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akievo

Akievo

作者 Akievo · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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当前安装
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在 OpenClaw 中安装
/install akievo
功能描述
Persistent project planning for AI agents. Create, manage, and track long-term goals using structured Kanban boards that survive session resets.
使用说明 (SKILL.md)

Akievo — Agent Plan Mode

You have access to Akievo, a structured project management system. Use it as your persistent memory and planning layer for long-term goals. Akievo boards survive session resets — they are your source of truth.

Core Principles

  1. Always check before creating. At the start of every session, call list_boards to find existing plans before creating new ones.
  2. One board per goal. Each major goal or project gets its own board. Prefix agent-created boards with [Agent] (e.g., [Agent] Launch SaaS Product).
  3. Lists are phases. Use lists to represent sequential phases or categories (e.g., "Research", "Build", "Launch", "Done").
  4. Cards are tasks. Each actionable step is a card. Include clear titles and descriptions.
  5. Respect human edits. The human may add, remove, reprioritize, or comment on cards. Always re-read the board before acting. Never undo or override human changes.

Session Start Pattern

Every time a new session begins:

  1. Call list_boards to find boards prefixed with [Agent]
  2. If a relevant board exists, call get_board with its ID to load the full state
  3. Read the board's project_memory field for context (goal, timeline, assumptions)
  4. Identify the next unblocked, incomplete task
  5. Report status to the user: what's done, what's next, any blockers

Creating a New Plan

When the user describes a new goal:

  1. Call list_workspaces to find available workspaces
  2. Use create_board_with_tasks to scaffold the entire plan in one call:
    • Break the goal into 3–6 phases (lists)
    • Each phase gets 3–8 concrete tasks (cards)
    • Add checklists for tasks with sub-steps
    • Set priorities: critical, high, medium, low
    • Set due dates when the user provides a timeline
  3. Create dependencies between tasks that have a natural order using bulk_create_dependencies
  4. Present the plan to the user and ask for feedback before proceeding

Working on Tasks

When executing on a plan:

  1. Pick the next unblocked, highest-priority incomplete card
  2. Work on it (using your other tools — coding, research, writing, etc.)
  3. Add progress updates as comments using add_comment
  4. When done, call complete_card to mark it finished
  5. If blocked, call block_card with a clear reason
  6. Move to the next task

Updating the Plan

As work progresses, the plan may need adjustment:

  • Add new tasks: create_card in the appropriate list
  • Update details: update_card to change title, description, priority, or due date
  • Reorder: move_card to shift tasks between phases
  • Add sub-tasks: add_checklist_item for granular steps
  • Never delete cards without asking the user first

Progress Reporting

When the user asks for a status update:

  1. Call get_board to get current state
  2. Count completed vs total cards per list
  3. Highlight blocked items and their reasons
  4. Identify upcoming due dates
  5. Suggest next actions

Important Safety Rules

  • Never delete a board without explicit user confirmation
  • Never archive cards without asking
  • Always re-read the board before making changes (the human may have edited it)
  • Log your work — add comments to cards explaining what you did and why
  • Stay scoped — only modify boards you created or were explicitly asked to manage
安全使用建议
This skill is internally coherent and appears to do what it says: manage persistent Akievo Kanban boards. Before installing, verify the Akievo service (akievo.com) is the legitimate service you expect and that the referenced repository/homepage are trustworthy. Create an API key with the minimum scopes required (prefer scoped read/write keys rather than full account-wide keys) and be prepared to revoke it if you see unexpected activity. Remember the agent may act autonomously by default — monitor initial runs and ensure the agent follows the SKILL.md rule to ask before deleting/archiving boards. If you have any doubt about the publisher, confirm the GitHub repo or company site listed in the README/skill.yaml before granting the API key.
功能分析
Type: OpenClaw Skill Name: akievo Version: 1.0.0 The Akievo skill is a legitimate project management integration that allows AI agents to maintain persistent Kanban boards via a remote MCP server (mcp.akievo.com). The instructions in SKILL.md and README.md are well-structured, focusing on task organization, respecting human edits, and maintaining an audit trail through comments, with no evidence of data exfiltration, malicious execution, or prompt injection attacks.
能力评估
Purpose & Capability
Name/description (persistent project planning) match the declared requirements: a single AKIEVO_API_KEY and MCP server pointing at mcp.akievo.com. Minor metadata mismatch: the top-level registry summary said 'Homepage: none' and 'Source: unknown', but the included files (README.md and skill.yaml) reference akievo.com and a GitHub repo — likely benign but worth verifying the publisher.
Instruction Scope
SKILL.md limits actions to board/list/card operations (list_boards, get_board, create_board_with_tasks, create_card, update_card, complete_card, etc.) and explicitly instructs to re-read boards and ask for human confirmation for destructive actions. It does not instruct reading local files, unrelated environment variables, or exfiltrating data to unexpected endpoints beyond the declared MCP server.
Install Mechanism
Instruction-only skill with no install spec and no code files — nothing is written to disk or downloaded during install. This is the lowest-risk install profile.
Credentials
Only a single environment variable (AKIEVO_API_KEY) is required and used as the Bearer token for the declared MCP server. That is proportionate for a service that needs read/write access to user boards. No unrelated secrets or config paths are requested.
Persistence & Privilege
The skill is not marked always:true and does not request system-level persistence. It can be invoked autonomously (default), which is expected for skills; SKILL.md includes user-confirmation rules for destructive actions but enforcement depends on the agent's runtime policy.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install akievo
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /akievo 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Akievo 1.0.0 — Initial Release - Introduces persistent project planning for AI agents with structured Kanban boards that survive session resets. - Boards are organized per goal, with lists as sequential phases and cards as actionable tasks. - Outlines robust workflows for session startup, goal planning, task execution, plan updating, and progress reporting. - Emphasizes respecting human edits, requiring confirmation before deleting boards or cards, and maintaining clear logs of agent actions. - Integration requires an AKIEVO_API_KEY for secure API access.
元数据
Slug akievo
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Akievo 是什么?

Persistent project planning for AI agents. Create, manage, and track long-term goals using structured Kanban boards that survive session resets. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 141 次。

如何安装 Akievo?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install akievo」即可一键安装,无需额外配置。

Akievo 是免费的吗?

是的,Akievo 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Akievo 支持哪些平台?

Akievo 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Akievo?

由 Akievo(@akievo)开发并维护,当前版本 v1.0.0。

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